{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Improving training stability"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = untar_data(URLs.MNIST)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(#2) [Path('testing'),Path('training')]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path.ls()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_data(bs=64):\n",
    "    return DataBlock(\n",
    "        blocks=(ImageBlock(cls=PILImageBW), CategoryBlock), \n",
    "        get_items=get_image_files, \n",
    "        splitter=GrandparentSplitter('training','testing'),\n",
    "        get_y=parent_label,\n",
    "        batch_tfms=Normalize()\n",
    "    ).dataloaders(path, bs=bs)\n",
    "\n",
    "dls = get_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 288x288 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dls.show_batch(max_n=9, figsize=(4,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def conv(ni, nf, ks=3, act=True):\n",
    "    res = nn.Conv2d(ni, nf, stride=2, kernel_size=ks, padding=ks//2)\n",
    "    if act: res = nn.Sequential(res, nn.ReLU())\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def simple_cnn():\n",
    "    return sequential(\n",
    "        conv(1 ,8, ks=5),        #14x14\n",
    "        conv(8 ,16),             #7x7\n",
    "        conv(16,32),             #4x4\n",
    "        conv(32,64),             #2x2\n",
    "        conv(64,10, act=False),  #1x1\n",
    "        Flatten(),\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai2.callback.hook import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit(epochs=1):\n",
    "    learn = Learner(dls, simple_cnn(), loss_func=F.cross_entropy,\n",
    "                    metrics=accuracy, cbs=ActivationStats(with_hist=True))\n",
    "    learn.fit(epochs, 0.06)\n",
    "    return learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2.308123</td>\n",
       "      <td>2.305305</td>\n",
       "      <td>0.101000</td>\n",
       "      <td>00:24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn = fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CeAu4OGKbnwLPquoOAFUNJNyfB0xS1RJ33SRgmIh0B9qq6kx1ottXgUsSrahNSmJMlZQOlj0ZUusEBcaYpqkyStCZEWX6+j5dWnNo59asGzM8bHn3drkAdG6T0yD121FWGQzE/zGtgDfnbACgZG9FgxzPNAsHARtC3he6y0IdBhwmIl+KyCwRGVbLvge5r2sqs84sDcOYKqkfLFvLsjEpyZvgje6JvQ/gf788mRtOODhJNQoX+tTqz59WpWIkIR3UNF/R/ngiT4RMnFSKM4BrgBdEpH0N+8ZTpnNwkZEiMk9E5hUXF9daWbu8GuOoPSGwCcsQsc44xqSoaC3LAX+95pganxo9cukALhp4EJ4MYfHGUgBGnJTHtBVFrEvSqBaxhpSzp1kmAYVAz5D3PYBNUbaZpaqVwFoRWYETPBfiBNCh+05zl/eopUwAVPV54HmA/Pz8Gv+QndEw7G/dGEgwWHY7HLwN5AHrgCsDeVYR200ETgC+UNULEzlmKEvDMCZ11dQ59wcDD4y6/H+/PJkWWR76dWsTXPajIb1onePh4oEHcd9FR5I3alxS6rd8y+6oy6cs38oJhx5A786tg8uGPjmdcq+fz39/ZlKObdLWXKCviBwCbASuBn4Usc3/cFqUXxGRTjhpGWuA1cAjIZ36zgVGq2qJiOwWkROA2cANwF8TrahgLcvGBCSahjEKmKKqfYEp7vtoHgeuT/BY1VgahjGpKzAaxnlHdo17n0E924cFyuB8D1x6TI+o+c6JeGZK9Fn+7vrgW85+Yjp+v6KqLNu8i1VFe/iuxMZpNjVTVS9wC/AJsAx4R1WXiMgDInKRu9knwHYRWQpMBe5Q1e2qWgI8iBNwzwUecJcB3Ay8ABTgBNUTEq6sZRsZE5RoGsbFVD0W+jfOI6E7IzdS1Skickbk8kRZy7IxqavC65y7N56Ux+/O7cfSJE19PeW3p7Np5z6uf3FO2PL7fnAEpx7WmZzMDE7509SEj/O3qQX06NCC299ZGFymqjw6YTlX5vekT5fW7CyrwJMhtMmtfbxo0zyo6nhgfMSye0JeK3C7+xO570vAS1GWzwOOSn5dk12iMakp0WC5q6puBlDVzSLSJQl1ipszg5+dzcY0FHdc2HnAxmSmUAHsr3RygltkeejbtQ19u7apZY/49O7cmt6dW/PIpQPYvqecJyat5LoTejHi5EOSUn7AZ8uLaJUTPiHKNxt28vzna5j47RY+//2ZDHpgEi2zPSx9ICnD3hrzvRFrWjYmqNZgWUQmA92irLor2ZURkZE4A6vTq1evWrfPsBn8jGlov8Z5XNw22QUHg+XsxGbgi+VHxzvfIT8/ozeZESkaH//qFERgb7mPr7/bwZgJy+tc/sLCndVa3n74968A+K6kjKcnO2kcZSEdBc976nO6tsvl1f8bEly2v9JHblbD/A6MqS8b9MWYKrXmLKvqOap6VJSfD4Gt7oDouP8W1Vxarcd6XlXzVTW/c+fOtW5vLcvGNBwR6QEMx8mFTLp9brCcm+B01bXJ8mRUG+7tqIPaceSB7RhySEd+fnrvepVb2336U5Orhpsr3VfJtxtLWbF1N5+vrBqy69uNpfS/eyKTlm6tVx2MaUg2g58xjkQ7+I0FAvPT3wh8mGB5dZKRIdhkWsY0mL8Avwca5CzbX+kU21Aty03JwPs/5cK/flFt+fz1zuBB01eGtzOU7quMOXSdMd8HwWbwMyYg0WB5DDBURFYBQ933iEi+iARbo0RkBvAucLaIFIrIeQkeFwBPhk13bUxDEJELgSJVnV/LdnWa5CDUzn3OTHitcxp/uPdPf3MaVw/uGbZs3Zjh5B3QEog9lF19fbRwE4sKdwa/vzwRLd8D7/+Uc56cDsDOsgrWFO9J6vGNqY2lYRhTJaFg2R3O5mxV7ev+W+Iun6eqPwnZ7lRV7ayqLVS1h6p+kmjFATwZGQnPAmaMiepk4CIRWQe8BZwlIq9FblTX1KlQa4r30qVNDq2aQLB8WNc2PHjJUdWGsbsi3wmg27VIbh1/9eY3XPS3L4NpZIFh7zaUlDHZTcnYuHMfABc8PYOznpie1OMbEw9rizLGkdLTXWdmCD6/5WEYk2yqOtq9sc3DmTjhM1W9LpnHKCjaEzaxR2PL8mRw7fHO1NnHHezM+1C6rxKAjq1yGuSYD41bBsDbczfg9fk59bGp/OTVeWHbbCrdH3d5pfsqWbBhZ1LraJonwWbwMyYgpYPlLI9Q6bWT2ZhUo6qsLt5Dny5NJ1gG6NAyG3BamgG6ts0FoH+36sPaXX5cj2rL6quswsfwZ6rnNNfVjS/N4ZJnv7SOWSZhloZhTJXGf/6ZgOxMD7vclh9jTMNQ1Wk4Ew4ljdev7N7vpUubhmmxra8BPdrxwg35nNK3EwAjTsrj8G5tGHJIx2rbHtKpVVKPvWJr9Om1Ayp9fnx+JTNDyPREb+cItCp7/UqWx6Idkxi75zLGkdIty9keocJraRjGpJpNbj5uTlbT+wo654iuwXGPPRnCSX06kenJ4Pnrj+PeHxzBTSfn8dWos4Itb7nuZ3j4UmcCtXYtkjdb355yb/D1wg076X/3xGppGqECdbIhNU2iRGw0DGMCUrxlOYNKGzvOmJTzm7cXALBsc82tqU3JuUeGz80UmOHshhPz+NVZfVDgrg++xedXHrj4SO75cEnCxxz2l8+Dry//50wApq0o5pHxy/hseRGTbz89ok5OgGMdn03i7MmEMQFNr1mnDrI8GVRYsGxMytlR5qRPpXJQF5jqumW2hza5WbR0W6OvHtyTG07M48Ub8xM+RuGOfVGXP//5GgqK9rCzrCJseYbbtOy170WTBJaGYYwjtVuWPRlUWhqGMSkrlduurh7ci9KySn562qEAZHoyWP7gMLLdfOKzD+/Kaz8+nutenN1gdTjtsak8+sOjEYELBnQPpmHUdhMyZ20JvTq2pFu73Aarm0ltzt+SRcvGQKq3LGday7IxqSjTHVe4RVbqzt6XnZnBr87uG8xvBsjN8gTHTAY4pW8nurVtuIB0134vv3zja37x+tdAVWpIZM6yquIPWXblczM5LyTFw5hIqXwja0yypXawnCFU+uzO15hUs6rImZHu98P6NXJNGl6HVtnfy3F8fg02HkT25fjZf+Zz6B/Gs31PeXBYudJ9ldXSOEzDE5FhIrJCRApEZFSU9SNEpFhEFrg/P3GXnxmybIGI7BeRS9x1r4jI2pB1g5JR12177O/DGEjxYDnTk2G9vo1JYR2/p0CyMe0NGdEC4IkrBgZf33RyXti6O87rxx+HH16v4wx9qmqWvz9NXMFjE5fz5pzv2LprP5+6swI+OmE5r83+LrjdmAnL63UsUz8i4gGeBc4HjgCuEZEjomz6tqoOcn9eAFDVqYFlwFlAGfBpyD53hOyzING6frhgE+CMwmJMc5fSOcuZGYLXZvAzJmVJM5j5IPKG/rLjevDbdxcCcOew/tw5rD/9754IwLG9OrB++956HWdNcdV+Hy3cFHwdekNS4fUzd21J8H3R7vJ6HcvU2xCgQFXXAIjIW8DFwNI6lnM5MEFVy5Jcv6DAsIUrtuxmYM/2DXUYY1JCSrcsezIEr6VhGGOasJdGDOaXZ/bmwYuP5KNbTgGgZ8cWgDOiTyDnuXfnVpzY+wCuyO/JDSceHNy/TW5ibRole6sepY9duImyCl/w/WfLiygts4mdvkcHARtC3he6yyJdJiKLROQ9EekZZf3VwJsRyx5293lKRKLO9iMiI0VknojMKy4ujqvCNuW1MSkeLGd6MvD61aZ2NcY0Wf26teGO8/pz/Yl5DOjRDoB3f3YS/7zuWDxuZ8BVD5/PpN84YyZ7MoTrT6gKlnt0aAnAkQe2TUp9Ji/bGvb+sn9+lZRyTVyiPUqJvIB9BOSp6tHAZODfYQWIdAcGAJ+ELB4N9AcGAx2BO6MdXFWfV9V8Vc3v3Llz/T6BMc1QagfL7oXG0paNMamkW7tchh3VPfg+y5MRNopG9/Ytgq9zszJY8dAw7orIZT7VnZI7UQVFe1BV/vfNRvZX+lBVXvlyLUW79ielfBOmEAhtKe4BbArdQFW3q2ogP+ZfwHERZVwJfKCqlSH7bFZHOfAyTrpHUlhblDEpHiwHWmVsFj9jUkvb3ExGnJTX2NVoslrnZPL2yBMAp1EgJ9ND3gGtguv/+4uTgt9/dZWdWf1rf9aaEm57ewH9757I9JXF3PfRUq7+16z6Vd7UZC7QV0QOEZFsnHSKsaEbuC3HARcByyLKuIaIFIzAPuJ0ArgE+DbJ9TamWUvpYDnLE31MUWNM01bu9ZMTJWgzVbq3c1qXz+jXBYADQ1qbj+3Vodr33kA3xaM2mVGC7DETquKxv09bDTgdBv/wweLg8g8XbOQn/54bfH/za/O5+vmZcR3TOFTVC9yCk0KxDHhHVZeIyAMicpG72a0iskREFgK3AiMC+4tIHk7L9HTCvS4ii4HFQCfgoaTVOVkFGZPCUno0DE+Gc7FN5SlzjWluVJ3xgC1YrlmvA1oya/TZdG0bta9WsHPzmB8OoGh3Obec2YdD/zC+1nJDO/gFLCwsDb6eEzJaxhuzv6Ng6x5+dHwvbnvbGY3shRlreGhcVXBdULSHc56czqe/OY3DuraJ78M1Y6o6HhgfseyekNejcXKQo+27jigdAlX1rOTWMrTshirZmNSR0lerQAuJ19IwjEkZlT5FNXo6gAnXrV1uzOH1Ai3LB7Zvwa1n9w3LeU6mOetKgoEyEBYoA4xdsBGAcYs2xyxj7roSrn1hln1XG2NSUoq3LFsahjGpptzrtGzmZKbuVNeNZd4fz8HvNvUFxpiP1UJ/dI923HRyHp8tLw4bdznZ9rot1a1yYv9//ubtBRTu2Mfm0v307Niywepiks+GjjMmxVuWAznLloZhTOoo9zpBnrUs112n1jl0aZMLwK79zqQRbXKzgutfuCEfgOMP6cjYW07h0mN6kBvj93zBgG5JqdOSTaXBeox6fxG/f29htW0yJDBykX1XG2NST0pfrYI5yzYxiTEp4735hQCs3Va/meqM47wjuwKQ16mqpbZVjvOwMPQbMdaTt2N7dUhKPWatcXKcW2Z7eGvuBt6ZV1htm0CGiLVrpB67vzEmwWBZRDqKyCQRWeX+W+3bV0QGichMt3fvIhG5KpFjhgrmLNuU18akjPnrdwAWLCfqt0P7seT+82iZXZVNF0xvDglwfDGinYwkTzX+t88Kwt4v3LCTh8ctZd66kuAsgk9OWskNL81J6nFNw7JY2ZjEW5ZHAVNUtS8wxX0fqQy4QVWPBIYBfxGRpEw0n2lDxxmTcs7q7wyF9vth/Rq5JqktI0OCLckB0cLfwPfj01cP4rJjewSXX3i0M5zvVfk9WfvoBQnXZ1XRnuDrZ6cWcPGzX/KvGWu5/J8zgykjHy3cxOcr45tm2TQR1rRsTMLB8sVUTcX5b5zB0MOo6kpVXeW+3gQUAUmZZzMzOCmJnczGpIpA8Na5dfQh0UziQjtlZXmcr/mczAzuPN+5QfnxKYfQpW0u68YM50+XHx11xI1T+lTNEHj70MP44s4z4z7+45+sqHF9bQ0cpWWV/P69hRTttlkEjTGNL9FguauqbgZnuk2gS00bi8gQIBtYneBxgaqcZWtZNiZ1BIYPCwRxJnmOPbgDPzzmIB67fGBw2d0XHsHPTj+Ucw7vSpc2ucz4/ZmMPr9/zDKO6N4WgJdvGhxcduvZfenRofooFhN+fWq96rlkUyl5o8Yxb13VmM5bd+0P/m38fXoB78wrZOK3W+pVvkkeu7oaE8fQcSIyGYjWbfquuhzInY7zP8CNqho1yVhERgIjAXr16lVrmZkey1k2JtUEngQFzl+TPFmeDJ68alDYso6tshl9/uHB97GGbuvUOptteyp4/IqjObxbWzIyhNHn92fGqm0xj3e4G1jX1a/e/AaAD77ZSH5eR7w+P8c/MoULBnTjF2f04bnpawCYvaaEG07MA2D3/kp27/eGzWRojDHfh1qDZVU9J9Y6EdkqIt1VdbMbDBfF2K4tMA74o6rOquFYzwPPA+Tn59d6Q5tp4ywbk3Iq/day3BTlH9yRiUu2kOXJCE5w8rPTe/Oz03sn/Vjrt5cBsECNJ6EAACAASURBVLfcyWUOjKgxfvEWxi+uak0et3gz9+8p5y+TVzJj1TbWby9jyf3nsWnnPvrabIHfC0tZNibxNIyxwI3u6xuBDyM3EJFs4APgVVV9N8HjhfFYzrIxKafS65yvFiw3LY9dcTRPXTWw3lNWDx/Qvc77/G/BJlZs2c11L86Ouc29Hy7htVnfBQPsn746j6FPfU7eqHHMWrO92vZenx+1CM8Yk0SJXq3GAENFZBUw1H2PiOSLyAvuNlcCpwEjRGSB+zMoenF1E7jYWsuyManD6/cjUnWza5qGtrlZXHpMjxq3ue2cvvzhguj5zs9ee2y9jnveXz6vcf2u/ZVh779aXRUgv/zl2rB1+yt99LlrAs9MqRrG7ra3vuGZKavqVTeD3XgYQ4LTXavqduDsKMvnAT9xX78GvJbIcWLx2DjLxqScCp/fWpVT1G3nHAY4E5p0ChnNJDfL+f985ppjuNXNR06WmnKmV27dQ96ocQzs2Z6fnXYoR/doB8Bbc7/j1+f0BZzWa3A6KRpjTH0kFCw3tix3NIwKrwXLxiSTiOQCnwM5ON8T76nqvcko2+tTsqxVOaXl53UMvv767qHBzpoXDTyQfl3bcP9HS8JagBtKYGKbhRt28ovXv2bMDwcA0CLLw5riPWEjOSzZVMqRB7Zr8DqlG2tXNibFp7tuleMBoKzC18g1MSbtlANnqepAYBAwTEROSEbBlT4/WZkp/dVjQnRslU3b3Kzg+37d2vCP647jj8MPD9vuiHqOnFEXO8qclI2cLA9nPTGds5+YHlw3/Jkv6HvX+AavQ21EZJiIrBCRAhGpNpGXiIwQkeKQtMWfhKzzhSwfG7L8EBGZ7c6m+7bbVygpLAvDmBQPllvnOg3ju90e1caY5FBHYEq2LPcnKZfNSp+SmZHSXz2mFu1aZHFi7wOC71c/cgHH9ErKxK01CoyusS7GVOqVPm3UHFwR8QDPAucDRwDXiMgRUTZ9W1UHuT8vhCzfF7L8opDlfwKecmfT3QH8OFl1tljZmBQPlgOtGc9NT8ocJ8aYECLiEZEFOENCTlLVakMWiMhIEZknIvOKi+ObxrjS5yfbxlhOe4GO10ce2DbuzpyJdvrcua8CgH2VsZ821mX0pK279uNPbgfyIUCBqq5R1QrgLZyZcOtNnOkXzwLecxdFnU233uUnqyBjUlhKB8u5WU4aRoeWSXviZIxxqapPVQcBPYAhInJUlG2eV9V8Vc3v3Dm+Wey9Pj+Z1sEv7XndIDMwHn5gRu0HLj6SgT2jtzKfFNIaXR+vzfqu1m12lFVEXf705FXkjRoXbHneUrqf4x+ZwpiJyxOqU4SDgA0h7wvdZZEuE5FFIvKeiPQMWZ7r3pzOEpFAQHwAsFNVA49YY5VZr5vbKDOhG9PspPwV64RDO9Ii29PY1TAmbanqTmAaMCwZ5VX6lCxrWU573dvlAnC+O/7y5cc5Md9pfTvz9sgTWHDP0LDtR5yUx6/OavgRK45/ZErwdaXPzwMfLeU3by/gqckrgao+MNv2lAPw/OdreGfehuoF1U+0P/zIpuuPgDxVPRqYjNNSHNBLVfOBHwF/EZHecZbpLKzHza0xJsVHwwCn1/O2PdFbCowx9SMinYFKVd0pIi2Ac3DyIhNWaUPHNQvd27Vg4T3n0raFc5kZ1LM968YMD67PzfLQv1sblm/ZzfQ7zuDgA1qxuXRfcH1mhgRbp5Mtb9Q4cjIzuPGkPF6KGKv5pDGf8fGvTuF37y4MLvvk2y1cmd8zspj6KARCC+oBbArdwB2SNeBfhJx3qrrJ/XeNiEwDjgHeB9qLSKbbulytzETYba0xaRAst8zOZF/lvto3NMbURXfg326HpAzgHVX9OBkFW7DcfLRrmVXj+gm/PhUAcZ/1d2/Xglmjz6ZljocWWR427thH4Y59Nc7wV1/lXj/Pf76m2vLSfZWc+tjUsGUZIbnU5V4fgpBdvxFd5gJ9ReQQYCNwNU4rcZCIdFfVze7bi4Bl7vIOQJmqlotIJ+Bk4DFVVRGZClyOkwMddTZdY0z9pXywnJvlYZ8NHWdMUqnqIpxWq6Qr9/rrG2iYNCNREmK7uekbAHmdWrG5dH/M/UeclEfrnEwKd5QFJx9pCLv3V/Ld9jJ6HdCS/AcnIwKL7juvzuWoqldEbgE+ATzAS6q6REQeAOap6ljgVhG5CPACJcAId/fDgedExI9zAztGVZe66+4E3hKRh4BvgBfr/2nDRfs/Mqa5SflgOTtTqPTZpCTGpIqSvRX06NCisathUoQ/ylBvvzyzNwN7tOfcI7sFlz111SAOGd0w4yjPWlPCaY9PZe2jFyQ8VKmqjgfGRyy7J+T1aGB0lP2+AgbEKHMNzkgbSWexsjFpECxneTIsWDYmhewoqwhOS2xMbY480JnM5IrjenD+gG4MOeQAWudUv3TFagHt0DIrOFlJokKDcRvVxZjmI+XPdCdYtmHTjUkVZRU+Wman/H26+Z60b5nNujHDefyKgZzVv2vUQDng/ZtPqrZs2u/ObJB6TV8Z39Brqc4alo1Jk2B5T7mXLTXktRljmo4Ky1k2DeS4gztwZX6P4Ps1j1xQrZNh+1o6HcZre5qPwvSXqwY1dhWMaTJS/oq10x1gfuR/5jVyTYwx8XBm8Ev5rx7TRD1y6QD+ce2x3HDiwcFRLLq1reo0+NSVNQeBJxzakcF5HYLvY80q2FDD2jUVp/TtBNh018ZAGuQsBzp/bNtd3sg1McbUxuvz41esZdk0mExPBucP6B6cDAVg2h1n4PMrrdwUjom3ncq4RZs58sB2nNGvM/PW7eC6F2dzTK/2vDXyRMAZixngnZ+dyGX/+KracRKcmbvJS/OPZ0ydpHywnOF26rC7X2Oavgq3M66Ns2y+T7lZ4bO89u/Wlv7d2gbfn9znAH4/rB+XDKo+S3S/bm2Cr0ed358xE5zpr9O8YTkoymAkxjQ7KR8sB3pAp/sjMWPSQaXXOU+tZdk0JSLCL87oE7Zs8u2nsWu/l5ZuoH3NkJ78/PTePP7JCnx+pcKb3uP7B66tatGyMakfLOdmORfdvQmOfWmMaXjlPifAsGDZNHV9ulS1KC+5/7xg6/SnvzmNs5+YHnxKkq4CaRgWKhuTBsFyK3cIqjKbxc+YJq/C6wQYOZaGYVJIq5Dh6gIT6gT+ltNVYNhqa1g2Jg1Gw/jpaYcChA0XZIxpmgJjomdlWvchk5oCI7lUpPn4/mJd/IwJSvlguV2LLNrmZobd+RtjmqZAa1y2x1PLlsY0TSJC/sEd6NImp7Gr8r1I71sCY+KTFhFmpicDn3XwM6bJCwbLlrNsUth7UWYKTDvBNAy7thqT0BVLRDqKyCQRWeX+2yHKNgeLyHwRWSAiS0Tk54kcMxpPhthoGMakgKqh4+wRrzFNmdgpakxQos07o4ApqtoXmOK+j7QZOElVBwHHA6NE5MAEjxsmM0PwpnnPZGPSgbUsm+ZORIaJyAoRKRCRatdMERkhIsVuA9MCEfmJu3yQiMx0G50WichVIfu8IiJrQ/ZJeK7q4GgY1g5lTMJpGBcDZ7iv/w1MA+4M3UBVK0Le5tAAedLWsmxMagi0LOdYsGyaIRHxAM8CQ4FCYK6IjFXVpRGbvq2qt0QsKwNuUNVVboPTfBH5RFV3uuvvUNX3klhXANSylo1JOHDtqqqbAdx/u0TbSER6isgiYAPwJ1XdlOBxw2RmiOUsG5MCKr02g59p1oYABaq6xm1Iegun0alWqrpSVVe5rzcBRUDnBqupMSao1iuWiEwWkW+j/MR1ggOo6gZVPRroA9woIl1jHGukiMwTkXnFxcVxfwhrWTYmNQRali0NwzRTB+E0GgUUussiXeamWrwnIj0jV4rIECAbWB2y+GF3n6dEJOGhOiwNw5gqtV6xVPUcVT0qys+HwFYR6Q7g/ltUS1mbgCXAqTHWP6+q+aqa37lz/DfMmRkZ+NJ8zEtj0kHV0HEWLJtmKVq3uciL10dAntvANBknxbGqAOda+x/gJlUNdNYZDfQHBgMdiUiHDNk37gap4KQkNW5lTPOQ6BVrLHCj+/pG4MPIDUSkh4i0cF93AE4GViR43DCZHmtZNiYVVFgahmneCoHQluIeQFhaoqpuV9Vy9+2/gOMC60SkLTAO+KOqzgrZZ7M6yoGXcdI9qqlLg1RgUhJrWTYm8WB5DDBURFbhdFgYAyAi+SLygrvN4cBsEVkITAf+rKqLEzxumH0VPuauK0lmkcaYBmAd/EwzNxfoKyKHiEg2cDVOo1NQ4Gmt6yJgmbs8G/gAeFVV3422jzi98i4Bvk20olUtyxYtG5PQaBiquh04O8ryecBP3NeTgKMTOU5t1mzbCzitVpYLaUzTZUPHmeZMVb0icgvwCeABXlLVJSLyADBPVccCt4rIRYAXKAFGuLtfCZwGHCAigWUjVHUB8LqIdMZJ81gAJH0+A2Oas7SYwS/A6/eTnfozeBuTtqyDn2nuVHU8MD5i2T0hr0fj5CBH7vca8FqMMs9KcjVDym6oko1JHWl1xar02lltTFNmOcvGpAabwc+YKml1xar02yx+xjRl+yp9ZHnEgmVjmriqDn7WCGVMWl2xysp9jV0FY0wNysq9tMxOq+wvY9JSsIOfxcrGpFewfMVzXzV2FYxJC+6sm1NFZJmILBGRXyej3L0VPlple5JRlDGmAVkWhjFV0qqJZ+uu8to3MsbEwwv8VlW/FpE2wHwRmaSqSxMptKzCSwsLlo1JGdawbEyatCz/7tzDGrsKxqQVd5KDr93Xu3HGeo02LW+dVHj95GRasGxMUydik5IYE5AWwXLfrm2qLftq9TbWuuMvG2PqT0TygGOA2VHWxT19LoDXr2R57AGvMU1d4Cy1SUmMSZNgOTtKz/of/Ws2Z/552vdfGWPSiIi0Bt4HblPVXZHr6zJ9LoDXp3gyLFg2pqmzDn7GVEmLYDkzpKXK57cz25hkEJEsnED5dVX9bzLK9Pr9ZGakxdeOMWktmIbRyPUwpilIi6tW6MW33GvDxxmTKHGulC8Cy1T1yWSV6/Nr2M2tMcYY09SlRbAc+ljX8pSNSYqTgeuBs0RkgftzQaKFVloahjGpxfIwjEmPYDl0Ws5R7y9uvIqkob3lXr75bkdjVyOpdu2vZM7aEpZsKsXrs1kfo1HVL1RVVPVoVR3k/oxPtFyfX232PmNShIilYRgDaRIshzZUleytaLyKpKFfv7WAS//+FTuawO91xZbd3PPht/gTzEu/+bX5XPncTIY/8wWPf7oiKXWburyIuetK6rXvosKd/OrNb9hQUpaUujRllT6/tSwbkyIEa1g2BtIkWJaQpuUTex/QiDVJTKXPz679lY1djTCLCncCUO6tewvsnnJvUj/Pj/89l1dnrmfjzn312v/hcUsZM2E5yzbvDi5btKE0KXW76ZW5XPHPmfXad9POfXy0cBO793uTUpemzOdXMi1YNiYliIgNHWcMaRIsZ4QEy7Euw8s272J/5fff+a9o934+XLAxrm1HvjqPo+/7tIFrVD9Sj/hm4P2fJvXzBB7fV7ipEze9PIe8UeNq3GdvuZc5a50W33/NWMs/p68O+xtZuXU34xdvrvXY+yp8cXUe3VzqBPJenz/u/Hmv21LeHMYfdjr4pcXXjjH1IiLDRGSFiBSIyKgo60eISHFIX4GfhKy7UURWuT83hiw/TkQWu2U+I1Kfb+wodU1GIcakgbS4aoWe0PuiBMQleys4/+kZjHp/Ub3Kn/jtlnoH2je9PJdfv7WAnWW1pzFMXVH7pA4NaVHhTsYu3FTrdte/OJsB934CwJriPdwbIzWitmH8VJVnpxZQtHt/XPULBJOVbrAc+H35/Yqq8/PkpJWs3FrVcnz7Owu48rmZFO+umgo99DKyfW8Fv3j961qPffg9Ezn/6RnB989OLQgeJzSIPvHRz9hX4eOR8cs588/TgsFzTQK/p+aQnlDp91vLsmm2RMQDPAucDxwBXCMiR0TZ9O2QvgIvuPt2BO4FjgeGAPeKSAd3+38AI4G+7s+wZNXZ0jCMSZNguXv73ODrfRXVg9q95c7j7Xnr695Rbf76En7+2nweHresTvvNWFVMudfHJjdloCmM/7xiy24e+ngpGuPb76K/fcmtb34TdZ1flWWbnTkpZqzaxu5yL+u372X4M1/w75nrWVW0B4CdZRWsKd4TV8e5xRtLefyTFdz+9sK46h9oWfb6wut/6B/Gc8jo8fzqzW94Zsoqzn3qc9Zvd1p1l29xAtpXvlob3L6+jS5rip0yy70+Hv9kBec+9TnPTV/N67O+C9tub4WXr1ZvA2DH3kpWbd0d9vvYX+njt+8s5LvtTo5ypft5msP4wz6fpWGYZm0IUKCqa1S1AngLuDjOfc8DJqlqiaruACYBw0SkO9BWVWeq8+X+KnBJMiprHfyMcaTF1blLm6pguSxKsFzbnfG3G0tjtqjuLHNybgt3xN/5anFhKde/OIdHxy8PftHECtAqfX6OuGciH3xTGFLf2r+eSssquePdhcEbgXjc+NIcXvhiLUUhray1CdTk71NXc/7TM/h2Y1WO7+mPT6vWkj/8mS8464npbNhR1aI6YfFmvizYVq3sQPrBnjg/QyBYjpU//fGiqnSK0x+fxi1vfI3H/b0/O3V1cF20/4kNJWWs2LI7yho49sFJwddfFmxj176q+j46YTkPfLw0bPuiXVW/3+9K9jL0qc+57J8zeW66U4cPvtnI+18X8tznznuf3/k8zWH84UobZ9k0bwcBG0LeF7rLIl0mIotE5D0R6VnLvge5r2srs87T0wtiLcvGkCbBcqiyKOkSgQ4KsRoUL/zrFzFbVAMCwe62PeWM/u/iGvNXd7gpF6uL9wS/aGIFwKX7Kimr8PHgx1Ut1+MWb+af01dH3T5QhzETl/Pu/EKOvPcTfvdufC2zAYFW7v2VvrDgtyaBkR42l9acMhHofBfaenjz619z7QuzY+4T73dxYFrz+etL4mq5/njR5qipDdFuFk59bCpXPjeTf3+1juHPzODlL9eSN2oclT5/2Agr174wm8EPT67xuLe8+TXfuSNbBNI/Fm7YyaMTlgNVfx+tczOBqpuG5tDi6nTwS7uvHWPiFe0kj/wK/AjIU9WjgcnAv2vZN54ynYV1nJ4ewTr4GUMaBsv7KsJbKa99YRbvfx1fB7toImPcR8cv58053zFuUexOYYGgXLUqSI6VhREoxx9yoFve+IYxbmAV6dmpBeQ/NJk351Q9+n9vfmHUbSMFAsdAzu+v3/qGC//6Ba/PXl/rvoF0hljh3EcLN4XlZUdLO1lcWHtgvr/Sx49fmcvq4j3V1mVlOkd/ZPxy+tw1odayoG55wKX7Krl37BKWbNrF/R85rcUzVtU9j3xDSVnVE44od2iBNJIsN2gM/K6aQ8c3GzrONHOFQM+Q9z2AsMeaqrpdVQN39P8Cjqtl30L3dcwy68vOVGMcCV2dRaSjiExye+ZOCulsEG3btiKyUUT+lsgxY5lz19mccGjHamkYXxZs55kpq5w61OPUD6ZRBN67QW08j6Y05J7cH7GDqjqd48YucdZHCS6Ldu1n1prtYcse/yT6uMA79laEpTM4rdrhZQaClP2VTrD8yZKtANz1wbfV6hZLrNb5v00t4If/+Cr43hvl8/zgb19E31mVDxdspNLnZ/baEqYsL+I+9/fyVcE2Rv93ETe/Np8vC7ZH378Gy2OkVsTr/16ZV+d9KkNyqiP//3aWVfD3aQWAM1JK/kOTgx0Fm0MQaUPHmWZuLtBXRA4RkWzgamBs6AZuDnLARUDgseMnwLki0sG91p4LfKKqm4HdInKCOwrGDcCHSauxNSwbk3DL8ihgiqr2Baa472N5EJie4PFi6tIml0M7t65x1IrQQE9V+XxlMac+9llw2bx1Jdz7YfTAsS59wgJBeWjMGdrSunbbXv40cQVnPVH164gWn17x3Eyufn5WXDnMxzw4idMemwo4KRNnPzGd12eHdzzLDAbLNY/sERroFkekLNT0ewh0gANipqm8MGNNcEbAQFELC0v59VsL+NtnBdW2/9ELs3lzzgYmfLulxjo3VZFPIE57bGrwZuWdeYVs21POa24HweYQRHpt6DjTjKmqF7gFJ/BdBryjqktE5AERucjd7FYRWSIiC4FbgRHuviU419G57s8D7jKAm4EXgAJgNRDfo7daWAc/YxyZCe5/MXCG+/rfwDTgzsiNROQ4oCswEchP8Jgx5WRmUF7pjxlchoYiT01eFWxxDrjcnVTi7guPiHJBrz2Q+c+s9ezZ7yWwqyrBiSaenVrAw5cOoHBHGWf+eVq1fSNbngHWu6MllFX4aJVT+39Vyd4KPvimMJhC8PV3O7juhIMBJ1jfusvJN47WQS40gK70+cnyZEQd7i7ekSSGPxO9Ffkhd1SRdWOGV1u3ddf+tH/st6uGiUeaQ8c3r8+GjjPNmztt/PiIZfeEvB4NjI6x70vAS1GWzwOOSm5NAx38LFw2JtFguav7CAhV3SwiXSI3EJEM4AngeuDsBI9XI48IPtWYKRKhgd7kpVtjllPh8weD5V+/tQBwhp8LHdHhP7PW88mSLTx/Q1Xsf/f/IlqlQ+7J3567ga5tc3ly0sqox4yW09wiy8O+Sh+l+yrJ8mTw7vwN1TeK8JuQYdj8IR35/vDfxex1U1T2lFefVa//3RODryu8ftZuK+XSv39VbbtkyRs1jv/8eEjYssj/t+Yw/XOodO/45vcrfm0eNwXGpAMRG2fZGIgjWBaRyUC3KKvuivMYvwDGq+qG2lolRWQkzsDq9OrVK87iq3g8gs+vrNhae57q9r2xh08bv3gLyzfv4o8XHhEcGm3mmu3MXLOdI7q3BWDBhp21HmPJxl3B1353woxYorUsB449btFmHh5ft3GeAQKpsze8NCc4ix04ebjRWnYD8h+aHDXnGGBdnLPSxSPQch4QenOxa7+XU920kuYi3Rtcm9OoH8akA8HSMIyBOIJlVT0n1joR2Soi3d1W5e5AUZTNTgROFZFfAK2BbBHZo6rV8ptV9XngeYD8/Pw6n6MeEcq9/rCZ1sLq6xyDbXsq2FPD4/DAUGw/P6N3tXVLN+8Ke//OvA2c0a8zQx6eUm3b3SEd7mqbkyTW2MFAvQJlgE+XbOHTJVvCAuV4xAqUgWCKR6Tu7XJrHVYuUuQNgl+rcqIXxnEzkm6SNENtk1U1U2F6t6Abky7S/TvJmHglmoYxFrgRGOP+W60HrqpeG3gtIiOA/GiBcjLEM5rA36etjjmiRKTHJ9a+3e/fW0T/bm3iKu/7Vu71M/I/86OuG/3f+k39HUuvji3rHCxXRNwg+FXDJvQw6cXrTr6SZWkYxqQMS8MwJvHRMMYAQ0VkFTDUfY+I5IvIC4lWrq5qC5bXbNvLhwviH3P57Xm15whD4sOTNYY358T32eIxOK8Ds+vYeg2wujgipUPht3WcYMWkjsD40s1hiDxj0oGThmHRsjEJBcvu4Olnq2pf998Sd/k8Vf1JlO1fUdVbEjlmTTxxPDJaubX6ZBcmMdmZ9fszCp1YBZyZC9PFTSfnNXYVmhxvM5p8xZi0YB38jAHSbAY/jz3ebRRZSQp+asrbjlfb3EQzi5Ljt+f2q9P2J/U+oIFq0nQE0jCsg58xqcHOVGMc6RUsW2eEpOnYKptZo+Mb6S+jCf3ebz6jDwAHtW+RlPLq+9FyQ1rbJ952aszt3vjp8UD06cHTjaVhGJNarIOfMY70CpbtIpw0GQLd2uXGte20FdEGQWkcN52cxys3DWboEV2TUl7gBuyO82K3FL/24+N59+cncsKhHfnlmb25/oSDw1IN+ndrW22f849yRmNskeUBap9VMR0E0jCsg58xqSE3K4O95bFHjjKmuUirYNnugpOnLr/L2hpFO7fJSaguA3u256mrBsa1bbYngzP6dYk53fYJh3ascf/Xfnx82PtAq3nn1rE/wyl9OzE4ryNvjTyRO87rz4OXVJ9I6/nrjwt7/+gPB7BuzHBaZjtpIxW+9G9Z9rlpGDZ0nDGpoWvbXIp22whFxqTVVWtL6b7GrkLaSGZKS2Ail7p66JKj6Nwmh39dfxyXHtMjrn0y3KcL+9zZCu/7wRG8+/MTg+vfGnli1P0CjjoovK6BX0NWZmK/j3OP7MbAnu2D7wNPQfp2ac2NJx7MX68ZlFD5qSDYsmxPgIxJCe1aZFG6r/qMr8Y0N2kVLBfX8w742uPrPltgU3fh0d2jLj8wztSKeFNaXrwxn5P7VO+c9ocL+vPTUw8B6j8D1MWDDmTuXefQpW18dQ5V4XNaMbu2zWVwXs2tyaE8GcJ/f3ES4LSIB34PyejE+M/rjg2+DkxtnZEh3H/xUfTp0jTH6k4my1k2JrXkZnmS0vHaNF9enx+vr/H+hj5bvjUpx0+rYHl3DbPy1SRZoznUpk+X1jWuP/HQ5I2IcM8Pjqi2rH+3NnGPGBJvw/LJfTpx1IHtqi0feVpv7hp+BOvGDEejjD1044kHRy3vs9+eHnwd+f/y2W9P54rj4mthvvvCI7h6cE/OPrx67vJXo87ik9tOizq8mydDOLZXB9aNGc7cu6omr6zP38jZ/bsw8rRDg++7t2vBoz8cQG5WRr2H20tlVTnLze+zG5OKcjIzYqa0GROP4x+ZwjEPTqrzftNXFlOZQJC7YMNO3p77Hf/3yjx+/lr0ydnqIq2uWqf361xt2YCDqgdykcsaajSHQOetgA4ts2rcPlqAG82pfTvVuk12jIDEF2dubLytf9G2i9WqHXBq305RA6Z1Y4ZzaOeqG4rIIcYO7dyahy49ioei5ATffEbvsI5j3du1YMxlR0cNSg9s34J+3dpw7w+OrJYiEvm3cN0JTlDfNaJ1e3gtnxHgxRGD+cMFh4ctu2ZIL5Y/eH6zbF0N3N03x89uTCrKyfRQXmkty6b+tu+tYPd+L6c/PpWbeAfo5gAAHJtJREFUowStE7/dwootuynavZ+Xv1zLhws2kjdqHDe+NId7xy4J27Zo9/7gzL9bSveTN2oc89fvCNtm/voSVJVLnv2SO99fDMDkZUUU7arbDMORmsagtEly/QkHc8+H4b/cyNmH1o0Zzg0vzQlb1lD9Ap+55hh++uq8kOPUfKDI4DqWeIKNWBM/xPtILdoNxBd3nkmWJ4PjH5lSVReRsME4XxqRz2l9q9+0ANxyZh9+eWYfWmR7eHTCsuDyW8/uS06UoDba58zJ9HDdCQfzx/99G1x2UPsW3DmsP3cO6x/z88wcfVYwDSDUU1cN4q+frWLc4s2oVv/cd5zXj5tP702WW78TDz2AmWu21z+3pBkLTkpiwbJpxkRkGPA04AFeUNUxMba7HHgXGKyq80TkWuCOkE2OBo5V1QUiMg3oDgQ67pyrqgkPU5STlWFpGClg7rqS4FPRAK/PT5+7JvDgJUdx/QnRn+TWReGOMtrkZtGuRexGP79f8asG44+CoqrZjddvL2P99jIA1m7bS05mBge0zg62+g7O68DcdeGB7xuzv+OAVtn89bMCrjiuB+/OLwRg4b3n8vnKYgBem7Weo3u044GPlrJp5z6mLC/ikE6tqtVt6ooirhpc/5TbtAqWowWj0WYfun3oYcFfNDTcwOuR5V527EHMqWFa6Jys+jX0n9KnE18UbAtbFisgKauoeqR22zl9+cvkVVG3ixbXd26TQ2lZeGePjAwJCxxP6t2pWqAeuBM8qc8BtMh2bgj6da3K0b196GEx6lD7/8w3dw+NK6Whe7vo4y7369aGv/3oWH5WWMrHizZVG9Ysy5NBh1bZgHOj9fGiTcxcsx1FOf2wzhzTq320YtOCiLwEXAgUqWr15vw68tkMfqaZExEP8CwwFCgE5orIWFVdGrFdG+BWYHZgmaq+Drzurh8AfKiqC0J2u1ZV55FElobR8DaUlDFtRRFd2+Zy7pHd6lXGFf+cCTjXKIClm3ZxYHvnaejD45ZWC5aXbd5F5zY5dIoY5Wncos0c3aMdPTu2BKDS56fvXRPo06U1BUV7OPiAltw+9DByszx0b5fLnyYuZ/76HSx/8HwA7vrfYt6cs4E/XTaAQzq15srnZkb9vGf+eRoQ/hQ6EEhH+utnBQDBQBlg4P2fMup8p3Hsg282snHHPuasq4qt1m7bW62cO99fbMFyTa7M78nCDTv57zcbg8sG9WzP+FtP5YJnZgBVIyjEY+rvzmBvuZcL//pFrdtGxulXDe4VfCwQqkPLLHaUVdYpl/PtkSfQsVU2Xdrm0jY3k0NGjw9bH6usc4/syocLNoUtu/Xsvlwy6EA6t8lhwH2fAnDTSXlh23Ruk0O2J4NOrXO4aOCBjF0YXkZAtNbgQGe70NbjS485iN6dW4eNEFEXj112NJkeCQayiRrQox0DelRP2Ykk7i2QKvz7/4Yk5dhN2CvA34BXk1FYpaVhGDMEKFDVNQAi8hZwMbA0YrsHgceA38Uo5xrgzYaqZECbnEz2lnvx+dXO2xj8fuW5z9cwfEB3eh3Qstbt91f6yHWfIi8uLOUHf6uKJdaNGc7abXv5x7QCHrl0QLBh4b35hUz8djNH92jP1YN71tjpfdXW3VzwzAza5DjhXWWUJ6rnPz2DDi2zeOaaY+jfrS2d2+RQ6fPzyze+BpyO+2cf3pX33QC1oGgP4AS0v35rQbXySssqKSjew5tzNgBEjXMClm7eFXz98aLNwdd1HaJwzITlwdehgXJDSdsmnsCjghbZHp68ahAHtsvlqvyewfWhjZZ1+Qo4pFMrjoqSBx0tjzZax7anrx7E6z85noKHzw8uu2jggQC0zol973LbOX3D0gyOP/QA+nZtQ7sWWYgIH/7yZC47tqrzW6wvtscvjz5e8aGdW9MmN4tX/28I4289letPzAtbP/eucxARMjKEZ645hpmjz2Lxfec6K0MOFW3IuUDLcranKs1ERGIGysfG0Vp75eCe/PDY+Dr7JVNzGspbVT8HkvYt9Mbs7wCblMQ0awcBG0LeF7rLgkTkGKCnqn5cQzlXUT1YfllEFojI3RLjsZyIjBSReSIyr7i4ONomYTq3zcWvsH1P0xhrOVkznY5btPn/2zvv8KiqtIH/TmZSCCQkAQIBQgqEJqEGCFWU0JQVu6KLIiou+6lY1oKuuGvvqOvqiuJa1sWy6KpYgrKwuNIVEZSEGjD0JoGAQMj5/rh3JjOZO5m0Se6E9/c882TuuWfueXNm3pn3nvMWMu/PdacYrQzd7s/lrws2uo+11qTe/SnjX1nK41/kMfTJBfxy9IT7/E87inhr6Vava6zbWUTn+77g8zWGkbh53xGfcf7w/mreW1nI6sJDXm1frdvDM1+up98j8+nz4Jf88d++Bunuol8ZMWMRAIfNYjKnSjUd7vmMEc/8lx5/nucugHXw6EkmzFrO5TOXoLXm+fllu8zXvmFsUOyr5Pt+5lMLuOilxZXqe8NbNQ+2qw45FsH+VaHBrix3axPLNxv3u48Xlyvd7OmbmmCxOjllWHteWrjJ7/X7pMQTG+VkQb7xhZNicUdppdbjerbxaZv+mzO4bWQn992mi7jocK4ZmMY/l2/ld2e2Z8km4/+xci3pkRzH08lx/HryFJ+u2enbwcTTZeGaQWls3lvMtYPS3G1DO1r7G5fHy63BlKdzqxjLVXqXS0hUJd1M3r4um8O/2jO3p8snbHy/hpduMNjM+2k3ICvLwmmN1Yff/Y2ulAoDZgAT/V5Aqf7AUa31Wo/mK7XW2033jTnABCx2hLTWM4GZAFlZWQEtz0SzoNTuouPVSuFZG0x9ZxXpzZuQ0iyaW9793r3qWV2enpfv3tqf9PoKZk/Odp9bunk/s5dv49nLenq5AZaWao4cL+HJ3HwmDkylcaTT7cu9zMO1ctuBo/y4o4j46Aj3zvVPO4r4/bD2XPHqUkZ0Mdwsprz9HVsePcfyt9y1yLZlXzHtEqIti3rtLz7BP5ZuY+LAVOKjy+wXz3giT0pKNRvM1eHO933hdW7T3mKfnWmA1Ls/tbyWFb8ctefvtQulqFFmDWjAK8tVyXDRNj6aJy/u7tWWbuEg7smcKQN5YFzZarJV9gmtdaUyVzjClKXTfPMmkUzNyWDZPTk+hrQ/nru8J2v/PAqAW3M6+s1M0bxJBE0bGdswTQNk6ags5/Vsbdn+whW9uXl4RsDUeS4aRTjq7Ys5EK2aRlHw2LmVvqlo6FR1pQrKckwLwmlIIZDscdwW8PRpiwG6AQuVUgVANvCxUirLo8/llFtV1lpvN/8eBv6J4e5RY1xZgPYcLssksKfoV8td05pwqlTzVG6+5Qr2R9/vYMZX6/nQdKV0rXp6smnvEZ6fv8FHroPFJ3z6ugxlgCWb97Oy4AArCw6w78hxJsxaxkff7+DXchlAVnpkXDjj/lyKj5e43Qs9KT5+iitfXeY2lAFmL9/GkCcW8POBY7z2zRZ3e4GFj+7Yv3zNd9t+AYzV5L4Pf+XTx5OcZxbR56GK+5xu3DGqk09b39QEjp2sme99g11ZdlEZk/mU1lySlUyvdvEsWr+XB+b+ZBlNWRHhFkFmWsNb1/av0h2a9+ur/oXkdITRxDTcp+ZkAHDo2DK+3lAWADj3psG0qmRxkkqhXH+sZzs5IdpvEJ8Q2lR1pQrAKW4YwunLCiBDKZUGbMcwfK9wndRaHwLcKyxmlos/uAL3zJXnS4ChHn2cQJzWep9SKhwjKLdWLCjPlWUw/GFHzFjE9LFdaRThYMPuI35Tni7euI9HPl/HB1MGBQzCfnHBRl5YsJH1uw8z8yrjvuBUqXa78IGRd9fFM/Py2bL/KHeN7sTgxxe42ydkpxDfOIKCfcUs2byfaR+soXOrGPJ2HaZ/WoLXKrCLi//mG4R24lQppcc1a7cf4vO1u3h9cYHX+QX5e8i2qIvgaQwHwipwcu32Ip+2qriKnC5ktmnKmu2HLM9NHJjKk7n5Xm1R4Q4OHfW9caoKDc5YdgXLuezMymRUGNnV2NLpkNiE9i0ac273JFrGRvHKVVlktmlK9qPWWxueeK4su95Il3tVZpumbgd5T76fPsJHvtgoJ0VmcZXylkd1q8ndNqKjl7Fs5XNdIySNmlAFJHWccLqitS5RSt0I5GKkjntNa/2jUuoBYKXW+uMAlxgKFLoCBE0igVzTUHZgGMqv1Ia8rmwJH32/nXs+LPORfWBuWTziVQNSyNt1mNHdvDM53PPhGgr2H+XNJQVcNySdt5ZuZemm/fz1SqOS6alSTeHBo3y+dhdPf7kegB2HjvHoZ+vo1S6O3/3jO79yPW+uDg8rt8N3stQwroeZ2RYA8nYZ6cusDGV/rNp2kIl/X+H3/I3/XGW5oPal6WpWGcbPXMrIroGzX3SZ/kXAPpVlzpSBlfYtrktmX5/N+FeWVrr/JzcN5r2VP4OGO+f84HWusUfs19JpwzmlNQ988iO7a5gvvMEZyw+dn8kf3l9dadeCji2beLk4KKXcW08julbsF+W58Ot55+yyf0vNDp/cNNjy9XHRvr7S828fxsqCA0x5+zsfI3RQh+bccGY61w1O93ldRQTbR3RMZhIvL9rMMIuiMELoopSaDQwDmiulCoH7tdazanpdSR0nnM5orT8DPivXNt1P32HljhdiuGZ4thUDfWpVSJMIp5EBqSJDc/Rzi/j1ZCmzrs7iyPES2iVE07xJpNvN4KFP13HdkHTuM3PjP1h8gq/W7WbW11vI333Y61prtxdZrq7640+feNdVeCo3n9qIAazIUHZhlZ6sKhw8epJ3V/4cuGMtcUGvNvRJiefNSf145LN19GgbF5TxuyTFsm5n5d9DgAHtvVfpuyTFsmnPEbery41ndeAFj+BKMDKdATyRm8e+I8aq8Rjzhu3lCX14+b+bSIyJJCxMkdA4osrZNsrT4Izlc7sncW73JG57z0hv4s9MLF+spCLmTBnAK4u2cPPwDK92Vx5D8F5ZvjQrmR8KD1UrB2+LmEg6tYoxZfTGEaaYNqaL74sCUHzc2MaJiQrO290zOc6d31FoOGitxwfjurKyLAihQ7GZVcEfLv9eT1/i6AjvGBvP6mm9q1H62B+Hf/WW7b2VhX56hj5Th2fw4sKNlqngPMl/aDTn/eUbrxuRyUPT3dVkh3Zs4Y65edyM1brgxW9YZfpKV0RiTKTb6LxqQAojurbkjcVbiXSG0SUphqfmrff5fo9whPG7Ye2JiXTSNy2Bi15azKyrs9w3JIvuOMur/6r7RtAowsGbSwp45LM8lk4bzg+FhmyOMMU7k73uFbkkK5mXFm5i9f0j3enyRp3RilEeOasfvdA7Jq06NDhj2cV1g9NZkLcnYCCWPz9bT/qkJNBnQoJPu9MRRoQzjBMlpV4+y0MymtfIeHS5ZtRWEIVrZbmXR3UfQagvxFgWhNChbXwjdyaFynK0nJ/ta98U1KJE9YPLxbM8beMbcceoTvxQeIhZ/yvzWZ5361BGmmncyrP8nuH085O5IveWoYx61vd1Nw/PYOrwDNLvMTYlJg1Ks/SRjnQ6eH/KACMw8sv1HCg+weShFe9Gvz6xH5v3HeHV/21hQd4eJg5M5UWLbGAf3TiIomMlaDSdW8UCMMSs2Lv65194at56NJqv7zyLIU8YvuQr/pjjlcBg0yPnADCuZ2taNY1y56aed+tQIp1lRcCuH5LOhOxUGkU42LjHMFXP69GavqnettgdIztx09kdiI4IrjnbYI3lrq1jWTV9ZPAHMu1Zz9yxreOsq8VVlrbxjchOT+D2kb5RndWhX1oCr03Mcn+oBaE+kWwYghA61IYb38L8GlferneWTBvulXZtxmU9UCjOyUwiwhnGuJ5t3Mby4A7N6dgyxsvAfmDcGWzZV8xZnRJJjI3ya0x3bNmENnGNOHbyFAc8snmUfx9axhr+5NcPSaNDYhPumrOGG0yjODYqnAnZKazaepAPVm33KghmRdPocHq1i+eF8cZu+PGSUhJjIpkwIJW8XUXc8s739E9PoFVsFElNA38ekhOiubxvMu+s+Nnv2M9d3qvc/x3jdayUclf8HdShGfee04VL+yZTnrAwFXRDGRqwsRyI2sp843LniDQLboQ7VJUD8MoT7gjjnckDaiybJ2d3rllCbkGoLSQbhiCEDpUJkg9E3q7DpDSLdpc0fnNSP656bXmlXntl/3bcktORJ3PzquRmcVlWMuN6teaKV4yK4VZ+r+W5c3Qnnvgi3/JcVLiDdydnc/v7qyk8eIwx3ZL8pnR98bdGEON3941g0usrmDAgxec3uGPLGPcO9PGSU3T6o2GIK6X45u6z2bjnMDnPLDLHLrMpnry4O11bx9IyNopvtx7k+qHpJMZEcVnfdj670Y9elMnUnAxioioXw+V6r6PCHUw06y+c0bopX952ZsDXuvJBD2pvJHN56Pxu3G5RP6I6KKW4PsDqeLA5bY3l2sL12Qx3Gh+yWiowJAgNlkCrHIIg2IfyC8sPX9CNez9ca93ZpGVspDvdnItSD0NuaMcWFDx2Ln/6+EeftGyenN+zNQ9fkGmOm8nuouNeKeQ8i4flPzSaRz/Lo2B/MQvz9xIWBgPbl9U56N7WfxaoCdkpRDrD+P2wDvx+WAd3+4mSUt5YXMBvzCq7/dOb8b+7zkZrbXkT8fGNgyjYf5RY0zhVSvH3awKnvI50+hqUHRJjeObSHmSnNyPOI2HBJR6ViF1p9lyUlynS6SClWdXS4FaX1nGN+PrOs0gy09I6HWGWBVVClRoZy0qpBOBdIBUoAC7VWh+06HcKcOWd2aa1Pq8m49YGZanlanYd1xdAuCOMpKZR3NrA8gk/fUkPmjegD7xQ/0g2DEEIHVKbNebHHUX87bd9eHvZVs7NTPJrLD94fjfSmjVmcEZzd30BV7qy3YeOM7Z7kle12+lju7qN5WsHp/HpDztZdOdZnCrVRDjDvAz1cEcYb0zqx+drdvKvbwuZn7eHW3M6MrxzIo0iHEQ6HfzpvDN4a0mBYSybP+7Tx3blgbk/0SUplqEdW9A/LYEnc/PpmhTLJVlt6ZDYxK+LYoQzzHJF099qe/e2cXRvW/XAfoD/3jHMHYzv4sLebat1rfoiOcG3knFDoaYry3cD87XWjyml7jaP77Lod0xr3bOGY9mSd28YwJxvC3GGKZaUK6ndELioT2gpqyAIglB7PH5xd8Z2T2J0t1buXMoX9m7DB99t55pBqby9dJs7xVev5DifPP59UuKZNCiNYZ1a+ATch4Upwh2Kk6c0d4zqxH1jrQuceDImM4kRXVty5HgJEc4wssoFfJ3ZMRH4kctM/9ZrBqVyYe82xEVH8OYkY5V3QPtmpDVr7A4mswN1tQIsVI+aGsvjMPKwArwBLMTaWG6w9E1N8InOFARBEISGQJNIJ2Myk7za2rdoAhjb/OsfHsPXG/Zy+3urSW9RZvA9emEm8WYtAX9V/sCocjt7+bYquWc5HWGWdQoA2jWL9spGpZTy6dtbMkMJVaSmxnJLrfVOAK31TqVUop9+UUqplUAJ8JjW+t81HFcQhBCiVJz5BaHB4PJCcAW4D8lowfJ7c7z6jO/XrlLXyk5vZlk6WhDsREBjWSn1FWBVk/HeKozTTmu9QymVDvxHKbVGa+2TxE8pNRmYDNCuXeUUrbq0Mp3Qz+/VJqjjCIIAJWIsC0KDoX+asZs6uEPzAD0FoWEQ0FjWWuf4O6eU2q2USjJXlZMAy2SKWusd5t/NSqmFQC/Ax1jWWs8EZgJkZWUF9dc1oXEEeQ+Olsh8QagDwh2KFffmeJWFFwQhNOmTkkDeg6NrJS2YIIQCNf3l+hi42nx+NfBR+Q5KqXilVKT5vDkwCPiphuPWClHhjlrJISkIQsUopWgRE+lVyUkQhNBFDGXhdKKmxvJjwAil1AZghHmMUipLKfWq2acLsFIptRpYgOGzbAtjWRAEQRAEQRAqokYBflrr/YBPvjSt9UrgOvP5YiCzJuMIgiAIgiAIQn0gDoSCIAiCIAiC4AcxlgVBEARBEATBD2IsC4IgCIIgCIIflNb2zH+qlNoLbA3QrTmwrw7EqQ52lU3kqhp2kitFa90icLf6IcR1VuSqGnaVC+wlm211VvQ1aNhVNpErMH711bbGcmVQSq3UWmfVtxxW2FU2katq2FWuUMWu8ylyVQ27ygX2li3UsOtc2lUusK9sIlfNEDcMQRAEQRAEQfCDGMuCIAiCIAiC4IdQN5Zn1rcAFWBX2USuqmFXuUIVu86nyFU17CoX2Fu2UMOuc2lXucC+solcNSCkfZYFQRAEQRAEIZiE+sqyIAiCIAiCIASNkDWWlVKjlVL5SqmNSqm763jsZKXUAqXUOqXUj0qpqWZ7glLqS6XUBvNvvNmulFLPm7L+oJTqHWT5HEqpVUqpueZxmlJqmSnXu0qpCLM90jzeaJ5PDaJMcUqpfyml8sx5G2Cj+brVfB/XKqVmK6Wi7DBnDQnR1wrls52+muPZUmdFX+sG0dkK5bOdzoq+BpeQNJaVUg7gr8AYoCswXinVtQ5FKAFu11p3AbKB/zPHvxuYr7XOAOabx5hyZpiPycBLQZZvKrDO4/hxYIYp10HgWrP9WuCg1roDMMPsFyyeA77QWncGepjy1ft8KaXaADcDWVrrboADuBx7zFmDQPQ1IHbUV7Chzoq+1g2iswGxo86KvgYTrXXIPYABQK7H8TRgWj3K8xEwAsgHksy2JCDffP4yMN6jv7tfEGRpi6EUZwNzAYWR8NtZfu6AXGCA+dxp9lNBkCkW2FL+2jaZrzbAz0CCOQdzgVH1PWcN6SH6WqEsttNX8/q21FnR17p5iM5WKIvtdFb0NfiPkFxZpuwNcFFottU55jZBL2AZ0FJrvRPA/JtodqtLeZ8F7gRKzeNmwC9a6xKLsd1ymecPmf1rm3RgL/B3c+vqVaVUY2wwX1rr7cBTwDZgJ8YcfEv9z1lDQvTVP3bUV7Cpzoq+1hmis/6xo86KvgaZUDWWlUVbnaf1UEo1AeYAt2itiyrqatFW6/IqpcYCe7TW31Zy7LqaRyfQG3hJa90LKKZsO8iKOnt/TR+ucUAa0BpojLFF5W98W3z2QgxbzJnoa5Wwpc6KvtYZtpg30dlKI/oaZELVWC4Ekj2O2wI76lIApVQ4hhK/rbX+wGzerZRKMs8nAXvM9rqSdxBwnlKqAHgHY5voWSBOKeW0GNstl3m+KXAgCHIVAoVa62Xm8b8wFLu+5wsgB9iitd6rtT4JfAAMpP7nrCEh+mqNXfXVNZYddVb0tW4QnbXGrjor+hpkQtVYXgFkmBGVERgO4x/X1eBKKQXMAtZprZ/xOPUxcLX5/GoMPytX+1VmBGo2cMi1NVKbaK2naa3baq1TMebkP1rrK4EFwMV+5HLJe7HZv9bv4rTWu4CflVKdzKbhwE/U83yZbAOylVLR5vvqkq1e56yBIfpqgV311ZTNrjor+lo3iM5aYFedFX2tA+rbabq6D+AcYD2wCbi3jscejLE18APwvfk4B8O3Zj6wwfybYPZXGJHFm4A1GJGhwZZxGDDXfJ4OLAc2Au8DkWZ7lHm80TyfHkR5egIrzTn7NxBvl/kC/gzkAWuBt4BIO8xZQ3qIvgaU0Vb6ao5nS50Vfa2bh+hsQBltpbOir8F9SAU/QRAEQRAEQfBDqLphCIIgCIIgCELQEWNZEARBEARBEPwgxrIgCIIgCIIg+EGMZUEQBEEQBEHwgxjLgiAIgiAIguAHMZYFQRAEQRAEwQ9iLAuCIAiCIAiCH8RYFgRBEARBEAQ//D/JQtBCkdrKAwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x216 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.activation_stats.plot_layer_stats(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.activation_stats.plot_layer_stats(-2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Increase batch size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dls = get_data(512)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2.309798</td>\n",
       "      <td>2.302868</td>\n",
       "      <td>0.098200</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn = fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.activation_stats.plot_layer_stats(-2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1cycle training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit(epochs=1, lr=0.06):\n",
    "    learn = Learner(dls, simple_cnn(), loss_func=F.cross_entropy,\n",
    "                    metrics=accuracy, cbs=ActivationStats(with_hist=True))\n",
    "    learn.fit_one_cycle(epochs, lr)\n",
    "    return learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.214023</td>\n",
       "      <td>0.079372</td>\n",
       "      <td>0.974100</td>\n",
       "      <td>00:08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn = fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.recorder.plot_sched()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.activation_stats.plot_layer_stats(-2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.activation_stats.color_dim(-2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.activation_stats.color_dim(-2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Batch normalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def conv(ni, nf, ks=3, act=True):\n",
    "    layers = [nn.Conv2d(ni, nf, stride=2, kernel_size=ks, padding=ks//2)]\n",
    "    if act: layers.append(nn.ReLU())\n",
    "    layers.append(nn.BatchNorm2d(nf))\n",
    "    return nn.Sequential(*layers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.127363</td>\n",
       "      <td>0.055647</td>\n",
       "      <td>0.986200</td>\n",
       "      <td>00:13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn = fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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2O/b7X7/pjr1/fbpefHwFMueub9f2ZW9fVZE5FZQptflIYlol3UGY/LJVFdP66x1IToRrVkEuThUNipG8SztSY3IwiYJ1A2ToZzqPEocjUmk5kPlI1j5QW6HParnlpr8fHG9MND79G0VaSpvFezwvNeJ8woJQfSdzQpFU1q7BuyS6ktuOsmspQ0nqYb8SyfPdKPk6SbCGukhsRQm3JshTGyiJHNOR4dT6owScT/0xYkl9ljQiepazH5zguFEr6nxN5wl1f5IgH45RfZcucaf385c7qePDiouIiIh8frjgERERkelxwSMiIiLT44JHREREpuezlJZHk5ZJUD7e95HG3/67V92x7Yt+bbh9eSpVHW77az6+AQl01ZerHtcBRMQjicZEIo4RJL6BmFtlOJIHSehNxFAS0w67LNE4Sl6ldFM4b3U7KBrjNc8XwQToMFq03hEJsXsYo/UNGPXUP8V2xWBtSoglKKm2FgmEUqoLpxc8C8sw2bcrEwr1mDpdBEwcb7hxTPwOnu9U/EbJPvjRw2IJ95iI0qPvpta3i0aDRHzsCzi3e24u+NFAJ35np0VJzvjug6roPXDA99/z13uyXUD90QPK+WFd9COXvlBU1ff4CY+IiIhMjwseERERmR4XPCIiIjI9n6XDQ74OeT31G8Bvf/Xzvsyy/xKw7oLeGu9eXo9hCCC6GVRXCb2ikCXyGML6Oyjsi3wdCokq11yset9lcKNv/A5+Re0Ch+CwP5WjltAuJPR6DsWDwV2Fwd84HM7/f8US7if1MGo5bFe61XDw/f0SylDQ2iFxXgb7/ruC552L1G2gdlTXYJUGudE9RYFscCjoQt71nqrPfJ1RywZepdQIOC/zPGopuu8l+ZHwbNF4V7+FnskDvHCp/XVuHoN3wFPU5yHtr9TFqffJ8xfepaGLk5C4PjQvV4m3+QP8hEdERESmxwWPiIiITI8LHhEREZkeFzwiIiIyPZ+ltEwcXz30x0qo4HLXC06Pr3vL7RGk5cc3ILkVaXn7mnYzDwXJIjViyCAJWigal7qDYKzWeKfsRIgkmTMNaeuEPJAOKTRvAX243pwG6aH4SN1KOzijMHxajgLsWDLN6k+ga46el0rRy/Vpv5KMHO/E3aUkZvezWsMO7VUiz5rwRHAbSZNBZYPiJom0LFj3x+p9ozCe7iQetuNaYN0orkO7ajm6n7QdMAfWi/NS+nIJ85DedaWtdD9reN/ug+BEfEaD3eVba20Nz1F3HorN1Nbz7aB5mP6oYvRd9xx+wiMiIiLT44JHREREpscFj4iIiEyPCx4RERGZns9SWqZU5fb7r7tDVVo+rHsZa397XkZurbX9XX9s96KIxn0RZP9Atlf5m3afpjDNYNdwEh/pvDTtt0pnJO2taMfoZDdlYLXqd/Wma1bJbQESYrpTL7Fen79vEvJubrK+6MuE4neaohyQXJNkQhYMQ2ExaAP1V51jkWT8RP3U/jq+mDqOCbHn25AK40SVlFMRf5REdG2ttd2u/8VB7R/s+zClu4q/aV2j7x3cbTx479A1+UcD/bEV/GijXnNFPziBdzeNB/3ApCbBY4I11L+Ej0vqD0zSfweI2meXvLu/r/PiGkREREQ+cVzwiIiIyPS44BEREZHpccEjIiIi0/NZSsu73/6uO7b8qz/rju1f3p78/U9fbboyj697EWr7qr/m/haSJu/KMUpF3ZBR2B9qVWzFVFSQySCRORFDKbmW5bvzothm09eVJu9iSmnQrtEUzksE33rucjku0VV5sIqD35Xp+3UF7d/uT+VEFmnHBehEUmcB87w4m6bGJgIp9SHVT/OV0ryT9qd9XcuNJm2n0P0QJKPW9qeSd9ZfqUx9Xninui557/SSbH/eBpLtk7rSdPLRH1pQW0k2p2sm45Y+H/W+E6H7qXb1snbW98/hJzwiIiIyPS54REREZHpc8IiIiMj0uOARERGR6fnkpWWSkQ//6393x6qg3FprX//x/cnfJChTqvIRloFUrmvDPchfkIrZQDReVpGS5DJKPCVBsohiiZT2VLlEmLtMBH7+76dYkWw53AqoP7inPfU9lFuScFvOpfshqK83RW4eFWlba20P4m9lSUmvwT0S1MtxH9bJAvOX7ofumwXPsVToZSzmnkL9lSWKZ2JoKoN3abnhe4GSd6sUTWI5C+99unpCXv/5Z4TeRTQP6Xmo8y59B9Pcr2emzxqP0fWSlvFdVJKV+R2QveTrM0n3cws/QHgOP+ERERGR6XHBIyIiItPjgkdERESm55NzeOpO6DvwdRb/+S+7Y+9+3js8h3p3tLtrf1rb38P3u+DdHGrwIIQMLiCoCkMFy/fA9C0nfe9MQVXJd/wp9N3tuhwjTwIdG/gOdl++KCd3htq/C1yT6ra01hplBe7Bk0juaRN6N3TftQ9XYejjaKjgAaQOumYUWhm29RBMOxoPOo/cjOoyoHtAjgq0leZKvSb5COk1kzbUOfFdZf2hxI26ASeJronP26rOzWyeJ88MGRdUf+KS4Xlnz3qmvsCF2+1hB3JoRz2WBn/S2NZ5gXPugnfFer07W6b++/RUua5doW+UPDP07+aH4ic8IiIiMj0ueERERGR6XPCIiIjI9LjgERERken50aTlKiO3xrueJ+f9///w0B17/6YXoWrQ4O6+K9J2L0FqvAHR6gF0uHpJkoppR1kKbivl0p1uE6k4lV95R+rzQV63mz4kjIU2CHyr1wu9tFsKYRysaw1jRNJnIosSo0F0KLcPhuH1qiXfD913BUVgmCc3MDfrzu6psDrah7ijNuz8jDJn3dH+Ameyytkb7EMKHoR+LWNE59GcXkK5RECn+um81ZKemdO/6V2xg/Hg5+/0bxLe12FgId1TrY/GO33X1XOpv6gN9F6jchWqn9rPkn0tQ89kNgc+JnQ/H9oGP+ERERGR6XHBIyIiItPjgkdERESmxwWPiIiITM+PJi2ToExC8vHVqZD8/k/edmX2sHP5ftNLVbu707+3ICh3acmttSPtcE4pyjXROBSUadfzmo5Mu+tSEmsiq40m6n53LqUVl7aGSazJjr7rsF1RMmfYhlTC7XYlh/rT3b8TRpXAdGxHU1BRdqak4jDRuFITb1vL+pXK0Dje32y7Y1Wmbq2f19RfyXlPnduXgaRikGTrNW/W/fWo71PBc136fwV2MNc/lphMgjLu4l7qGn0HtNbaCvqsvotI9EdoN/ZaBMqs4QKUfL2DeVHhZzJLu8/eF+ffh631Y5S+b0d3A0gTrL+/9tBVRERERD4jXPCIiIjI9LjgERERkelxwSMiIiLT86NJywSJzIt//5cnf3/zR5uuzONLEJRfQv1FUj7ckrQMwi0lJoPktlyfT0euMnJrrW2gXBX+MCn1irIXyXHXhIQ2EjxJ+KtcIidW0vteBOJpOh6JuHnJ2FZxb/S81lg8rbJ8mjhN913blkqUnL58Wm5HqcQwD6mvR5+Hm5vH7tiHipQf2obV+lRkpvuhvkiptXE6bya8VwEdfyBAcwDaRTL7aLvoByC1HP7IgtoV9A/VlQq9XXI+tIH+Ib/mDzuo7/E5KuXSd0U6bt154Q9mvi//QaVFREREPkNc8IiIiMj0uOARERGR6fmD7pZ++BJCBTena7AjLMnevwWH5wG+Gy7ODvo6N+Bq3IBjA05NDa8ih+dm3QeH0S6/9XtycmDou+Lke+D0u9z0u/qRNrTW2i30xWhd6ffyyXkYkDf4/XfyHXxrrS3LN/GHMJ5wBTsZbw+nbhS1oV6vtXH/i/4/idq1gdDK6rfQfVNd+2V/zTpu9Myk430b+CGpj0CzMJmbl1yzcgu7hj8eeocO50rgnxCjoZW3Yd+MekkUIIj+SVDXx37vjL5vUx8vYdR5am187hDV2xu9nx/iJzwiIiIyPS54REREZHpc8IiIiMj0uOARERGR6fnRpOV3f/HHUbl//JPTrdDf/YJCBiFo6wWIrS+KiEiCMgQK0m7mmw0JySVUC6Qq2gk4ESRHBeLWWlsX6XNH5jeQyq5VHkuC9VrLJNk0iC6R9DBAa9yh60iEz9ZYtqzlSJLOhdvzMvg1wxvXqOWOkfTNd8fGpOJb+LFBes1OioYQ0VHxlJ6ZVMpMRFB6PmieJM/bJc9MV39YF77/wt3eRxl9P9G41TFa0o0HP165hNEAzHSMsvma/dtAP1So/47RDxzo36fLWyMiIiLyGeOCR0RERKbHBY+IiIhMjwseERERmZ5npWVKR07Y/uqX3bHDuheO3r/tL19TlGkX9P1Nf6wTlFtri/vTYwuQ3tYgI9/ebvu6+kt2u55T0usGxC4qVyGJi0gEyQ0In6OyJbYB7qcKZ61lacK44zUk9iYCW5penJIIciSIU0ppIuTdLHvJdHeEtNzSrmU4dw7QVjq3llvTeMRpvKd1URI5tWtUWKTz7kDeveZcSZ6tdE6PJvum0PNW67/kXXFJ0u7HZHh37sG0+7SuhE9lPJK+uAn/7UnqT3/E8WydH1RaRERE5DPEBY+IiIhMjwseERERmR4XPCIiIjI9H5y0fHz10B3bffHq5O/9PcnI/bFvvujXW7tSPSUo71/30mEVlFtrbVVSlG9ARl5DEuv9TV+OUiVXRap6sXnsyhCjEmuaKplKq/15g9Jymi4cnHsTLsGpD7t00ysKhnQuCqWtn4ejAiP14YtVP8dqufx+0jTv8xJrMh6ttXaz2p4tk6Qqt8b9c02SfkxFytG6yKWuUjc973kqeyB9QhGer71QXwX3UVk4JRXxkdIMqouEfW7H2D1F/RPMie/qgnkRpFVfNB7JqeF8qsfShPTn8BMeERERmR4XPCIiIjI9LnhERERkep51eB7/9Kvu2PZFf8ruxem66dtf9OsoyEtrWwgVfHxTduJ+gO8hX/QOz92L3m2ofg7tXE7BZzcUpEcBguX7XAoTo+980122E8jrGfUF0u/Xq1+EbVhlO69nfsv5MLzWeLf6Uaj+/jv+rA8ThwB9AfDLiDqHyaVAwu/SKxiuiGN0/gv9S0L0kv655jzHNgz6ckQafrhs/TsrqSt1AEdDGJOxvGaQ4rXvp3cAM1+HSEJQqf1J+GQ659CzovfmYIDn6HnU/qRd6b8pz+EnPCIiIjI9LnhERERkelzwiIiIyPS44BEREZHpeVZa/vrf3nbH9je9hLQvxd79oi+ze4AAwfteXqqS8vJlHwL44uF9d+xu04t86yIf34GgfAs7J5NERztX112XSRKrYnNrre1B3NskYmsojiW7zKZce8fxEfAewwCwUQ7H68moCXQ/owF2NJfScaS5WQM2NxCuSKRS5rXadUkbknLUBoLadU2JtZbbkmB/Reh+RvsiPW+k7qf42G1N+idta0LaLnoPbD7R5y99pyTter49IiIiIpPjgkdERESmxwWPiIiITI8LHhEREZmeM9Iy7GZ+15fbl2OHW0h4hMTk4x1IVa9OheSH+z5B+cVtf2wDonHdvZySkG9AWr5b9aI0CWA1RTmRFZ8iSS/+2KQiZZUkryk1pnwK/ZOKfEm59H4otXlHMeZBG2hOkwCbtDU5L20XMVrXJXOzcslO3PXcdZjiS9esP4RYQrJ2vEP4YBtu4H1L5bqU4CumoacJ7Glba33J/bSW76CegAnv9XowfdMfx4wyOvcp9Z2Slq85X5/DT3hERERkelzwiIiIyPS44BEREZHpccEjIiIi0/O8tPwViIJLSE7cnB473oKU9NDLwS9e9PLxy7tTaZnSkV/eQNIyiMZVUn5Yk+zcy14kFG7gWJJ6m5S5BJLoRpOVqa1UV83f3oI0ewPzJGHVMnltf8W1eppo3AmYYTdTuWReUF/Qfd8vTuc1jUfahiUkTCdtXUNSatr+a5HO+3Tc+vrHpeUKieYorgf10zvsminXq1CwpnKJjJ/+WCIiHI8lJOd34xvKtYloHHNFefeq//akcn4ZyxX8KIgYHe8Pff78hEdERESmxwWPiIiITI8LHhEREZkeFzwiIiIyPc9Ky4cvesl3sYLE4fXpsdUaUo/vetH44aYXjauQ/PrmXVfmHgRlPLY8bT+lfJKMvApFKDp3lH0R31LBsJ5HUDtJbEXpM5Bd1yC6XhOUikGSHZX0Ysm7FEvPu6Y8mNz38nX46/MAAAWRSURBVAgyciikJ9MurYvK3bZTiTGVmKO+hiKjQjqxh/NGJfubRSZzUv312V2H90PliKQv0jld66Lz0j6s0DuM3nU0x1CoH/0hwUf+YUq95iXi/8f+IcHHbOs12uknPCIiIjI9LnhERERkelzwiIiIyPQ86/B8+eU/RJXcb079GdqV/H7dOzZ3cOzN5tvT88DNuYXQqBdLCBUs3+du4DxiBSFIH3s3V/o+OiEJvSLPh77rHvWG0roS34hYhTssj9af5rF1bsMFmxFXl4G8sdH7ScdxFYYRJk5HWldXBpwkJLilUSfpqXLVGbhf9O+i9LldB55K6ldUR+va4aaJd5Oc11pry8EA0gRy1Yh16EvVMfpDhKAmJHPpQ0j6cdjZCl3LxLWj+/5Q/8tPeERERGR6XPCIiIjI9LjgERERkelxwSMiIiLT86y0/B/f/l1UyaYIlyQar0FkfrP+tjt2WwSzu2VfF0myGxDTark0UHAJItQhWBuSZEpCGwlaVbqmMlzX2Jr13bEfepK192BzjorSkXga7pxM5a4ZBEkkEnE6xyokv1Jd0a7CF8jUxGFRRcTxnbjruZfslF3P3ZAMecl8CoTqUdk8nidQbDMoAsdtHZ0/w7vQj4VDjvZDCrWLdqanebI9nD7Pl4jf9ZrpjxnSYNT6g4PL2no8W4agsazzdfhHKT/AT3hERERkelzwiIiIyPS44BEREZHpccEjIiIi0/OstPyfXv+/qJIqu1Iq8R2klJJovCrCFJYB6ZAFz8PZMrEABmvD5NxU+n0s0uphEV4vSIhlKRDEbEpk7qtv+8V5EY3qor6gsUyguhJGJe/Wetl1VFBurR/LKuv/GMSJzEkh6NdEuk7bQCTtojKptFzHKB1v3LF7UGTerM7Xdck8pL64piwa1XVBGnbCqFB/ifxPuwEkbINZnSbbY/r5BT84oNr6a56ON/2QgEh+XLC8wo9S/IRHREREpscFj4iIiEyPCx4RERGZHhc8IiIiMj3PS8v3//ejXjzZ2j2VWhMJ9zHTL2Phtgp4JDZXGbm11rbQ7VVES6XcLSQmd6m9JDbTPYIojcJzJ0WTvNYLZreDcmUqU1dQGB+UpFtr7bakfqfzJIHmLzEqXVP92wOkbQ+OUZqOPHreNRON6TwSQUfviUiEy7Stta40TXo0uTuVRaN2jKaHt4+TvPtDavsvGf9EBB4dIxSUP6Bt1zo3bX9y3iWJ6x+Cn/CIiIjI9LjgERERkelxwSMiIiLT86zD8+ebr7tjyTf8+2P23Rt9M5zUv4Xq2bE5PbYNdy6nYD3azbqWI5+GuIHvxKvrQ44K1o/BjOW7brhv2hF+Retf+Cr6sbTjEI0aU3fmpfHA77WD3ZSra9TaZQ5PnWPkxaT/B5G0A70eCh0rLkMc8AjhaFQu8ZLSIMvkPAI9rsFwN7om3Xfi1aWOYdKHSRsuqYug+keu92NQ58BFQZDBPV0SUropbUvrqufRuVSG+Ni+32bZhwmP1k9treUuGY/v67y4BhEREZFPHBc8IiIiMj0ueERERGR6XPCIiIjI9Dxr2f6b1cPVLrQ90g6vIEcdqyjYy3fvj/15jyBKH4rYuqXzYM1HcjOxHJT5EmEOBcnFY3eMROZaKhaUQSNPhGcKUhyFdvilNlBoZT0Xg6tQ+s3GMQs7zObOqDydiMyJAPhUObzmoOBJ4ZNJu5Ar7JT8L6RCbyUZ/6eofTjaBmrHx5apP5n/Kw7mQDr36Z56KRrCKAefIxJ80+evtiNtQ/L8pWxW76NrJqJx+mOMoTJn+GTmsoiIiMjHwgWPiIiITI8LHhEREZkeFzwiIiIyPYtjmIosIiIi8rniJzwiIiIyPS54REREZHpc8IiIiMj0uOARERGR6XHBIyIiItPjgkdERESm558BV/KC55LBD0kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.activation_stats.color_dim(-4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.183244</td>\n",
       "      <td>0.084025</td>\n",
       "      <td>0.975800</td>\n",
       "      <td>00:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.080774</td>\n",
       "      <td>0.067060</td>\n",
       "      <td>0.978800</td>\n",
       "      <td>00:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.050215</td>\n",
       "      <td>0.062595</td>\n",
       "      <td>0.981300</td>\n",
       "      <td>00:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.030020</td>\n",
       "      <td>0.030315</td>\n",
       "      <td>0.990700</td>\n",
       "      <td>00:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.015131</td>\n",
       "      <td>0.025148</td>\n",
       "      <td>0.992100</td>\n",
       "      <td>00:12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn = fit(5, lr=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "jupytext": {
   "split_at_heading": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
